package com.atguigu.gmall.realtime.app.dws;

import com.atguigu.gmall.realtime.app.func.KeywordUDTF;
import com.atguigu.gmall.realtime.beans.KeywordBean;
import com.atguigu.gmall.realtime.common.GmallConstant;
import com.atguigu.gmall.realtime.utils.MyClickhouseUtil;
import com.atguigu.gmall.realtime.utils.MyKafkaUtil;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

/**
 * @author Felix
 * @date 2022/12/13
 * 交易域：来源关键词聚合统计
 * 需要启动的进程
 *      zk、kafka、flume、clickhouse、DwdTrafficBaseLogSplit、DwsTrafficSourceKeywordPageViewWindow
 */
public class DwsTrafficSourceKeywordPageViewWindow {
    public static void main(String[] args) throws Exception {
        //TODO 1.基本环境准备
        //1.1 指定流处理环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        //1.2 设置并行度
        env.setParallelism(4);
        //1.3 指定表执行环境
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);
        //1.4 注册自定义函数到表执行环境中
        tableEnv.createTemporarySystemFunction("ik_analyze", KeywordUDTF.class);

        //TODO 2.检查点相关的设置(略)

        //TODO 3.从kafka的页面日志中读取数据 创建动态表  指定Watermark以及提取事件时间字段
        tableEnv.executeSql("CREATE TABLE page_log (\n" +
            "  common map<string,string>,\n" +
            "  page map<string,string>,\n" +
            "  ts BIGINT,\n" +
            "  rowtime as TO_TIMESTAMP(FROM_UNIXTIME(ts/1000)),\n" +
            "  WATERMARK FOR rowtime AS rowtime - INTERVAL '3' SECOND\n" +
            ")" + MyKafkaUtil.getKafkaDDL("dwd_traffic_page_log","dws_traffic_source_keyword_group"));

        //TODO 4.过滤出搜索行为
        Table searchTable = tableEnv.sqlQuery("select page['item'] fullword,rowtime from page_log \n" +
            "where page['last_page_id']='search' and page['item_type']='keyword' and page['item'] is not null");
        tableEnv.createTemporaryView("search_table",searchTable);
        // tableEnv.executeSql("select * from search_table").print();

        //TODO 5.对搜索内容进行分词(UDTF)，并将分词的结果和表中其它的字段进行关联
        Table splitTable = tableEnv.sqlQuery("SELECT keyword,rowtime\n" +
            "FROM search_table,LATERAL TABLE(ik_analyze(fullword)) t(keyword)");
        tableEnv.createTemporaryView("split_table",splitTable);
        // tableEnv.executeSql("select * from split_table").print();

        //TODO 6.分组、开窗、聚合计算
        Table reduceTable = tableEnv.sqlQuery("select \n" +
            "    DATE_FORMAT(TUMBLE_START(rowtime, INTERVAL '10' second), 'yyyy-MM-dd HH:mm:ss') stt,\n" +
            "    DATE_FORMAT(TUMBLE_end(rowtime, INTERVAL '10' second), 'yyyy-MM-dd HH:mm:ss') edt,\n" +
            "    '"+ GmallConstant.KEYWORD_SEARCH +"' source,\n" +
            "    keyword,\n" +
            "    count(*) keyword_count,\n" +
            "    UNIX_TIMESTAMP()*1000 ts\n" +
            "from \n" +
            "   split_table group by TUMBLE(rowtime, INTERVAL '10' second),keyword");
        // tableEnv.createTemporaryView("reduce_table",reduceTable);
        // tableEnv.executeSql("select * from reduce_table").print();
        //TODO 7.将动态表转换为流
        DataStream<KeywordBean> keywordBeanDS = tableEnv.toAppendStream(reduceTable, KeywordBean.class);

        //TODO 8.将流中的数据写到Clickhouse中
        keywordBeanDS.print(">>>");

        /*keywordBeanDS.addSink(JdbcSink.<KeywordBean>sink(
            "insert into dws_traffic_source_keyword_page_view_window values(?,?,?,?,?,?)",
            new JdbcStatementBuilder<KeywordBean>() {
                @Override
                public void accept(PreparedStatement ps, KeywordBean keywordBean) throws SQLException {
                    //给问号占位符赋值
                    ps.setObject(1,keywordBean.getStt());
                    ps.setObject(2,keywordBean.getEdt());
                    ps.setObject(3,keywordBean.getSource());
                    ps.setObject(4,keywordBean.getKeyword());
                    ps.setObject(5,keywordBean.getKeyword_count());
                    ps.setObject(6,keywordBean.getTs());
                }
            },
            new JdbcExecutionOptions.Builder()
                .withBatchSize(5)
                .build(),
            new JdbcConnectionOptions.JdbcConnectionOptionsBuilder()
                .withDriverName(GmallConfig.CLICKHOUSE_DRIVER)
                .withUrl(GmallConfig.CLICKHOUSE_URL)
                .build()
        ));*/
        keywordBeanDS.addSink(
            MyClickhouseUtil.getSinkFunction("insert into dws_traffic_source_keyword_page_view_window values(?,?,?,?,?,?)")
        );
        env.execute();
    }
}
